Building responsible AI is only half the story. Stakeholders need clear visibility into how responsibly the system is ...

Existing frameworks for explainable artificial intelligence (XAI) and AI governance, such as the EU AI Act and the NIST AI ...

In a research study published this month in JAMA, computer scientists and clinicians from University of Michigan examined the use of artificial intelligence to help diagnose hospitalized patients.

Researchers developed a system that converts AI explanations into narrative text that can be more easily understood by users. This system could help people determine when to trust a model's ...

Clinicians who were asked to differentiate between pneumonia, heart failure, or chronic obstructive pulmonary disease (COPD) had a baseline accuracy of 73% (95% CI 68.3-77.8), which rose to about 76% ...

AI models in health care are a double-edged sword, with models improving diagnostic decisions for some demographics, but worsening decisions for others when the model has absorbed biased medical data.

When making diagnostic decisions, radiologists and other physicians may rely too much on artificial intelligence (AI) when it points out a specific area of interest in an X-ray, according to a study ...

A new study finds that clinicians were fooled by biased AI models, even with provided explanations for how the model generated its diagnosis. AI models in health care are a double-edged sword, with ...